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The geographical imbalance of the health workforce in Tanzania represents a serious problem when it comes to delivering crucial health services to a large share of the population. The
Tanzanian health system, like many others in low-income countries, needs better incentive
systems to attract dedicated workers to the health sector, to bring more qualified health
workers to rural areas, and to induce them to use their knowledge and skills efficiently.
However, creating better incentive and recruitment systems requires thorough knowledge of
health workers’ motivations and preferences, as well as the relative valuations of different job
attributes. The aim of this Ph.D. project has been to contribute to the base of knowledge about
health workers’ individual motivations and preference structures. It has also been an
important goal to examine how jobs with different characteristics can be matched with these
preferences in order to provide high-quality health services on a larger scale.
The first essay, ‘How to make rural jobs more attractive to health workers: findings from a
discrete choice experiment in Tanzania’, published in ‘Health Economics’ (2010), provides
new quantitative information about how health authorities can make jobs in rural areas more
attractive to newly educated clinical officers. A data set stemming from a discrete choice
experiment with clinical officer finalists in Tanzania is applied. The results show that offering
additional education after a certain period of service is one of the most powerful recruitment
instruments the authorities have available. Increased salaries and hardship allowances are also
likely to substantially increase recruitment in rural areas. Offers of decent housing and good
infrastructure, including the provision of equipment, can also increase recruitment to rural
remote areas but not as much as higher wages and offers of education.
In the second essay, ‘Mixed logit estimation of willingness to pay distributions: a comparison
of models in preference and WTP space using data from a health-related choice experiment’,
co-authored with Arne Risa Hole, different approaches to modelling the distribution of WTP
are compared using mixed logit models and the same data set as in essay 1. The standard
approach of specifying the distributions of the coefficients and deriving WTP as the ratio of
two coefficients (estimation in preference space) is compared to specifying the distributions
for WTP directly at the estimation stage (estimation in WTP space). The results suggest that
sensitivity testing using a variety of model specifications, including estimation in WTP space,
is highly recommended when using mixed logit models to estimate willingness to pay
distributions.
In the third essay, ‘How does additional education affect willingness to work in rural remote
areas?: an application to health workers in a low-income context’, the main objective is to
evaluate the effect of offering education opportunities as a strategy to recruit health workers
to rural areas. A dataset capturing stated job preferences among freshly educated Tanzanian
health workers with basic and more advanced clinical education is applied in order to
investigate how additional education as an incentive mechanism affects the willingness to
work in rural areas. In order to control for selection effects into the additional education
scheme, the two cadres are matched on propensity scores. It turns out that the health workers
with advanced clinical education would have been more likely to prefer a job in a rural remote
area had they not received the advanced clinical education. The result goes a long way in
suggesting that a policy aiming at recruiting health personnel with basic clinical education to
rural remote areas by offering jobs that include possibilities of upgrading after a certain period
of service, may be a temporary measure only.
The fourth essay, “Pro-social preferences and self-selection into the public health sector:
evidence from economic experiments” co-authored with Ida K. Lindkvist, studies the extent to
which differences in pro-social preferences are related to career choices. We test whether
preferences vary systematically between Tanzanian health worker students who prefer to
work in the private health sector and those who prefer to work in the public health sector.
Despite its important policy implications, this issue has received hardly any attention to date.
By combining data from a questionnaire and two economic experiments, we find that students
who prefer to work in the public health sector have stronger pro-social preferences than those
who prefer to work in the private sector. We also show that the extent to which these students
care about others can be conditional and linked to inequality aversion. A systematic selfselection
of pro-socially motivated health workers into the public sector suggests that it is a
good idea to have two sectors providing health services: this can ensure efficient matching of
individuals and sectors by allowing employers in the two sectors to use different payment
mechanisms tailored to attract and promote good performance from different types of health workers.

Has part(s)

Paper I: Health Economics 20 (2), Julie Riise Kolstad. How to make rural jobs more attractive to health workers. Findings from a discrete choice experiment in Tanzania, pp. 196–211. Copyright 2010 John Wiley & Sons, Ltd. Full text not available in BORA due to publisher restrictions. The published version is available at: http://dx.doi.org/10.1002/hec.1581